Extraction of fractional vegetation cover in arid desert area based on Chinese GF-6 satellite

Author:

Deng Zhengdong1,Lu Zhao1,Wang Guangyuan1,Wang Daqing1,Ding Zhibin1,Zhao Hongfei2,Xu Haoli1,Shi Yue1,Cheng Zijian1,Zhao Xiaoning1

Affiliation:

1. Defense Engineering College, Army Engineering University , Nanjing 210007 , China

2. Postdoctoral workstation of Jinling Hospital , Nanjing 210016 , China

Abstract

Abstract The red edge band is considered as one of the diagnosable characteristics of green plants, but the large-scale remote sensing retrieval of fractional vegetation coverage (FVC) based on the red edge band is still rare. To explore the application of the red edge band in the remote sensing estimation of FVC, this study proposed a new vegetation index (normalized difference red edge index, RENDVI) based on the two red edge bands of Chinese GaoFen-6 satellite (GF-6). The FVC estimated by using three vegetation indices (NDVI, RENDVI1, and RENDVI2) were evaluated based on the field survey FVC obtained in Minqin Basin of Gansu Province. The results showed that there was a good linear correlation between the FVC estimated by GF-6 WFV data and the FVC investigated in the field, and the most reasonable estimation of FVC was obtained based on RENDVI2 model (R 2 = 0.97611 and RMSE = 0.07075). Meanwhile, the impact of three confidence levels (1, 2, and 5%) on FVC was also analyzed in this study. FVC obtained from NDVI and RENDVI2 has the highest accuracy at 2% confidence, while FVC based on RENDVI1 achieved the best accuracy at 5% confidence. It could be concluded that it is feasible and reliable to estimate FVC based on red edge bands, and the GF-6 Wide Field View (WFV) data with high temporal and spatial resolution provide a new data source for remote sensing estimation of FVC.

Publisher

Walter de Gruyter GmbH

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

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